Evolving Connectionist Systems

From the combination of knowledge and actions, someone can improve their skill and ability. It will lead them to live and work much better. This is why, the students, workers, or even employers should have reading habit for books. Any book will give certain knowledge to take all benefits. This is what this evolving connectionist systems tells you. It will add more knowledge of you to life and work better. Try it and prove it.

[1]  An Introduction to Biophysics , 1929, Nature.

[2]  R. Fisher THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS , 1936 .

[3]  Harvey Fletcher,et al.  Speech and hearing in communication, 2nd ed. , 1953 .

[4]  D. D. Greenwood Critical Bandwidth and the Frequency Coordinates of the Basilar Membrane , 1961 .

[5]  R. Brown,et al.  Smoothing, Forecasting, and Prediction of Discrete Time Series , 1965 .

[6]  J. MacQueen Some methods for classification and analysis of multivariate observations , 1967 .

[7]  S. Grossberg On learning and energy-entropy dependence in recurrent and nonrecurrent signed networks , 1969 .

[8]  Marvin Minsky,et al.  Perceptrons: An Introduction to Computational Geometry , 1969 .

[9]  吉川 清隆,et al.  Perception of Speech , 1970 .

[10]  Michael A. Arbib,et al.  The metaphorical brain : an introduction to cybernetics as artificial intelligence and brain theory , 1972 .

[11]  G. C. Tiao,et al.  Bayesian inference in statistical analysis , 1973 .

[12]  Richard O. Duda,et al.  Pattern classification and scene analysis , 1974, A Wiley-Interscience publication.

[13]  I︠a︡. Z. T︠S︡ypkin,et al.  Foundations of the theory of learning systems , 1973 .

[14]  A. Dickinson,et al.  Brain damage , 1974, Nature.

[15]  James S. Albus,et al.  New Approach to Manipulator Control: The Cerebellar Model Articulation Controller (CMAC)1 , 1975 .

[16]  John A. Hartigan,et al.  Clustering Algorithms , 1975 .

[17]  C. Smith,et al.  Adaptive Coding of Monochrome and Color Images , 1977, IEEE Trans. Commun..

[18]  E. H. Mandami Application of Fuzzy Logic to Approximate Reasoning using Linguistic Synthesis , 1977 .

[19]  E. de Boer,et al.  On cochlear encoding: potentialities and limitations of the reverse-correlation technique. , 1978, The Journal of the Acoustical Society of America.

[20]  Stan Davis,et al.  Comparison of Parametric Representations for Monosyllabic Word Recognition in Continuously Spoken Se , 1980 .

[21]  S. S. Culbert,et al.  Cognition and Categorization , 1979 .

[22]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[23]  Stephen Grossberg,et al.  Studies of mind and brain , 1982 .

[24]  Stephen M. Mount,et al.  A catalogue of splice junction sequences. , 1982, Nucleic acids research.

[25]  H. Carter Fuzzy Sets and Systems — Theory and Applications , 1982 .

[26]  Stephen Grossberg,et al.  Absolute stability of global pattern formation and parallel memory storage by competitive neural networks , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[27]  B. Moore,et al.  Suggested formulae for calculating auditory-filter bandwidths and excitation patterns. , 1983, The Journal of the Acoustical Society of America.

[28]  Takayuki Ito,et al.  Neocognitron: A neural network model for a mechanism of visual pattern recognition , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[29]  J. J. Hopfield,et al.  ‘Unlearning’ has a stabilizing effect in collective memories , 1983, Nature.

[30]  ‘‘Cortical Sensory Organization. Vol. 3. Multiple Auditory Areas’’, by Clinton N. Woolsey , 1983 .

[31]  Michio Sugeno,et al.  An introductory survey of fuzzy control , 1985, Inf. Sci..

[32]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[33]  A. Wolf,et al.  Determining Lyapunov exponents from a time series , 1985 .

[34]  James L. McClelland,et al.  On learning the past-tenses of English verbs: implicit rules or parallel distributed processing , 1986 .

[35]  Tom Michael Mitchell,et al.  Explanation-based generalization: A unifying view , 1986 .

[36]  James L. McClelland,et al.  Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .

[37]  E. Lewis An Introduction to the Mathematics of Neurons , 1987, Trends in Neurosciences.

[38]  Farmer,et al.  Predicting chaotic time series. , 1987, Physical review letters.

[39]  S. Grossberg,et al.  ART 2: self-organization of stable category recognition codes for analog input patterns. , 1987, Applied optics.

[40]  James Gleick,et al.  Chaos, Making a New Science , 1987 .

[41]  Yves Chauvin,et al.  A Back-Propagation Algorithm with Optimal Use of Hidden Units , 1988, NIPS.

[42]  Bernard Widrow,et al.  Adaptive switching circuits , 1988 .

[43]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[44]  R. Hecht-Nielsen,et al.  Neurocomputing: picking the human brain , 1988, IEEE Spectrum.

[45]  Patrick Gallinari,et al.  Multilayer perceptrons and data analysis , 1988, IEEE 1988 International Conference on Neural Networks.

[46]  T. Deacon Human Brain Evolution: I. Evolution of Language Circuits , 1988 .

[47]  Stephen Grossberg,et al.  Nonlinear neural networks: Principles, mechanisms, and architectures , 1988, Neural Networks.

[48]  S. B. Kater,et al.  Calcium regulation of the neuronal growth cone , 1988, Trends in Neurosciences.

[49]  Geoffrey E. Hinton,et al.  A Distributed Connectionist Production System , 1988, Cogn. Sci..

[50]  Wendy G. Lehnert,et al.  Symbolic/Subsymbolic Sentence Analysi: Exploiting the Best of Two Worlds , 1988 .

[51]  Michael C. Mozer,et al.  Skeletonization: A Technique for Trimming the Fat from a Network via Relevance Assessment , 1988, NIPS.

[52]  Jerome A. Feldman Structured neural networks in nature and in computer science , 1988 .

[53]  T. Sejnowski,et al.  Predicting the secondary structure of globular proteins using neural network models. , 1988, Journal of molecular biology.

[54]  Didier Dubois,et al.  Possibility Theory - An Approach to Computerized Processing of Uncertainty , 1988 .

[55]  F C Hoppensteadt,et al.  Intermittent chaos, self-organization, and learning from synchronous synaptic activity in model neuron networks. , 1989, Proceedings of the National Academy of Sciences of the United States of America.

[56]  John Moody,et al.  Fast Learning in Networks of Locally-Tuned Processing Units , 1989, Neural Computation.

[57]  Stefan Wermter,et al.  A Hybrid Symbolic/Connectionist Model for Noun Phrase Understanding , 1989 .

[58]  S. Renals,et al.  Phoneme classification experiments using radial basis functions , 1989, International 1989 Joint Conference on Neural Networks.

[59]  Ken-ichi Funahashi,et al.  On the approximate realization of continuous mappings by neural networks , 1989, Neural Networks.

[60]  H. de Garis 'COMPO' conceptual clustering with connectionist competitive learning , 1989 .

[61]  M. West,et al.  Bayesian forecasting and dynamic models , 1989 .

[62]  Halbert White,et al.  Neural-network learning and statistics , 1989 .

[63]  Christian Lebiere,et al.  The Cascade-Correlation Learning Architecture , 1989, NIPS.

[64]  Daniel J. Amit,et al.  Modeling brain function: the world of attractor neural networks, 1st Edition , 1989 .

[65]  Andy Clark,et al.  Microcognition: Philosophy, Cognitive Science, and Parallel Distributed Processing , 1989 .

[66]  Geoffrey E. Hinton,et al.  Phoneme recognition using time-delay neural networks , 1989, IEEE Trans. Acoust. Speech Signal Process..

[67]  Li-Min Fu Building expert systems on neural architecture , 1989 .

[68]  Igor Aleksander,et al.  Introduction to Neural Computing , 1990 .

[69]  David E. Rumelhart,et al.  Predicting the Future: a Connectionist Approach , 1990, Int. J. Neural Syst..

[70]  W. Pitts,et al.  A Logical Calculus of the Ideas Immanent in Nervous Activity (1943) , 2021, Ideas That Created the Future.

[71]  Jude Shavlik,et al.  Refinement ofApproximate Domain Theories by Knowledge-Based Neural Networks , 1990, AAAI.

[72]  Teuvo Kohonen,et al.  The self-organizing map , 1990 .

[73]  Yoichi Hayashi,et al.  A Neural Expert System with Automated Extraction of Fuzzy If-Then Rules , 1990, NIPS.

[74]  Steven L. Salzberg,et al.  Learning with Nested Generalized Exemplars , 1990 .

[75]  Brian R Glasberg,et al.  Derivation of auditory filter shapes from notched-noise data , 1990, Hearing Research.

[76]  Shun-ichi Amari,et al.  Mathematical foundations of neurocomputing , 1990, Proc. IEEE.

[77]  Sylvie Thiria,et al.  Cooperation of neural nets for robust classification , 1990, 1990 IJCNN International Joint Conference on Neural Networks.

[78]  Catherine L. Harris,et al.  Connectionism and Cognitive Linguistics , 1990 .

[79]  Michael Gervautz,et al.  A simple method for color quantization: octree quantization , 1990 .

[80]  Richard P. Lippmann,et al.  Review of Neural Networks for Speech Recognition , 1989, Neural Computation.

[81]  Sholom M. Weiss,et al.  Computer Systems That Learn , 1990 .

[82]  D. D. Greenwood A cochlear frequency-position function for several species--29 years later. , 1990, The Journal of the Acoustical Society of America.

[83]  H. J. Arnold Introduction to the Practice of Statistics , 1990 .

[84]  Stephen Grossberg,et al.  ART 3: Hierarchical search using chemical transmitters in self-organizing pattern recognition architectures , 1990, Neural Networks.

[85]  Andrew W. Moore,et al.  Acquisition of Dynamic Control Knowledge for a Robotic Manipulator , 1990, ML.

[86]  Michio Sugeno,et al.  Fuzzy systems theory and its applications , 1991 .

[87]  Anders Krogh,et al.  Introduction to the theory of neural computation , 1994, The advanced book program.

[88]  W. Freeman The physiology of perception. , 1991, Scientific American.

[89]  G. Altmann Cognitive models of speech processing , 1991 .

[90]  Christopher L. Scofield,et al.  Neural networks and speech processing , 1991, The Kluwer international series in engineering and computer science.

[91]  Kurt Hornik,et al.  Approximation capabilities of multilayer feedforward networks , 1991, Neural Networks.

[92]  Michael C. Mozer,et al.  Learning explicit rules in a neural network , 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.

[93]  David G. Stork Sources of Neural Structure in Speech and Language Processing , 1991, Int. J. Neural Syst..

[94]  James A. Hendler,et al.  Integrating Neural Network and Expert Reasoning: An Example , 1991 .

[95]  John A. Barnden,et al.  Encoding techniques for complex information structures in connectionist systems , 1991 .

[96]  C. A. Murthy,et al.  A modified metric to compute distance , 1992, Pattern Recognit..

[97]  Piero P. Bonissone,et al.  Automated fuzzy knowledge base generation and tuning , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[98]  Stephen Grossberg,et al.  Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps , 1992, IEEE Trans. Neural Networks.

[99]  Martin Anthony,et al.  Computational learning theory: an introduction , 1992 .

[100]  James C. Bezdek,et al.  A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain , 1992, IEEE Trans. Neural Networks.

[101]  Vera Kurková,et al.  Kolmogorov's theorem and multilayer neural networks , 1992, Neural Networks.

[102]  J. G. Taylor,et al.  From Wetware to Hardware: Reverse Engineering Using Probabilistic RAMs , 1992 .

[103]  Atsuyuki Okabe,et al.  Spatial Tessellations: Concepts and Applications of Voronoi Diagrams , 1992, Wiley Series in Probability and Mathematical Statistics.

[104]  Babak Hassibi,et al.  Second Order Derivatives for Network Pruning: Optimal Brain Surgeon , 1992, NIPS.

[105]  Jacek M. Zurada,et al.  Introduction to artificial neural systems , 1992 .

[106]  Volker Tresp,et al.  Network Structuring and Training Using Rule-Based Knowledge , 1992, NIPS.

[107]  Erkki Oja,et al.  Principal components, minor components, and linear neural networks , 1992, Neural Networks.

[108]  Noam Chomsky,et al.  The Minimalist Program , 1992 .

[109]  Madan M. Gupta Fuzzy logic and neural networks , 1992, [Proceedings 1992] IEEE International Conference on Systems Engineering.

[110]  Xiaolin Wu,et al.  Color quantization by dynamic programming and principal analysis , 1992, TOGS.

[111]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1992, Artificial Intelligence.

[112]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..

[113]  L. Tsimring,et al.  The analysis of observed chaotic data in physical systems , 1993 .

[114]  Russell Reed,et al.  Pruning algorithms-a survey , 1993, IEEE Trans. Neural Networks.

[115]  Hugo de Garis,et al.  Circuits of Production Rule GenNets , 1993 .

[116]  Hilbert J. Kappen,et al.  On-line learning processes in artificial neural networks , 1993 .

[117]  Adi R. Bulsara Bistability, noise, and information processing in sensory neurons , 1993, Proceedings 1993 The First New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems.

[118]  J. M. Williams,et al.  Correlations between immediate early gene induction and the persistence of long-term potentiation , 1993, Neuroscience.

[119]  James J. Buckley,et al.  Are regular fuzzy neural nets universal approximators? , 1993, Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan).

[120]  John H. Andreae,et al.  The chaotic self-organizing map , 1993, Proceedings 1993 The First New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems.

[121]  A. Ralescu,et al.  Recognition of and reasoning about facial expressions using fuzzy logic , 1993, Proceedings of 1993 2nd IEEE International Workshop on Robot and Human Communication.

[122]  L O Hall,et al.  Review of MR image segmentation techniques using pattern recognition. , 1993, Medical physics.

[123]  Kaoru Hirota Fuzzy and Image Pattern Recognition , 1993 .

[124]  Stephen I. Gallant,et al.  Neural network learning and expert systems , 1993 .

[125]  Teuvo Kohonen,et al.  Physiological interpretation of the Self-Organizing Map algorithm , 1993, Neural Networks.

[126]  Wilfrid S. Kendall,et al.  Networks and Chaos - Statistical and Probabilistic Aspects , 1993 .

[127]  Richard J. Mammone,et al.  Growing and Pruning Neural Tree Networks , 1993, IEEE Trans. Computers.

[128]  Robert A. Jacobs,et al.  Hierarchical Mixtures of Experts and the EM Algorithm , 1993, Neural Computation.

[129]  Philippe Gaussier,et al.  A topological neural map for on-line learning: emergence of obstacle avoidance in a mobile robot , 1994 .

[130]  L. Medsker,et al.  Design and development of hybrid neural network and expert systems , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

[131]  Madan M. Gupta,et al.  On the principles of fuzzy neural networks , 1994 .

[132]  Mark S. Nixon,et al.  Generating-shrinking algorithm for learning arbitrary classification , 1994, Neural Networks.

[133]  Mahesan Niranjan,et al.  On-line Q-learning using connectionist systems , 1994 .

[134]  Andreas S. Weigend,et al.  Time Series Prediction: Forecasting the Future and Understanding the Past , 1994 .

[135]  A. van Ooyen,et al.  Activity-dependent neurite outgrowth and neural network development. , 1994, Progress in brain research.

[136]  Pierre Comon,et al.  Independent component analysis, A new concept? , 1994, Signal Process..

[137]  Jude W. Shavlik,et al.  Knowledge-Based Artificial Neural Networks , 1994, Artif. Intell..

[138]  Li-Xin Wang,et al.  Adaptive fuzzy systems and control - design and stability analysis , 1994 .

[139]  C. L. Giles,et al.  Constructing deterministic finite-state automata in sparse recurrent neural networks , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

[140]  Gerald Sommer,et al.  Pattern Recognition by Self-Organizing Neural Networks , 1994 .

[141]  Bart Kosko,et al.  Fuzzy Systems as Universal Approximators , 1994, IEEE Trans. Computers.

[142]  Maurice Crosland,et al.  The nature of knowledge , 1994, Nature.

[143]  Yoshiki Uchikawa,et al.  An efficient finding of fuzzy rules using a new approach to genetic based machine learning , 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

[144]  Kevin Bluff,et al.  Genetic optimisation of control parameters of a neural network , 1995, Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems.

[145]  Les E. Atlas,et al.  The challenge of spoken language systems: research directions for the nineties , 1995, IEEE Trans. Speech Audio Process..

[146]  Patrick van der Smagt,et al.  Introduction to neural networks , 1995, The Lancet.

[147]  James L. McClelland,et al.  Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory. , 1995, Psychological review.

[148]  S. J. Sinclair,et al.  The development of the Otago speech database , 1995, Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems.

[149]  Brian MacWhinney,et al.  The Handbook of Child Language , 1995 .

[150]  Gerald Sommer,et al.  Dynamic Cell Structure Learns Perfectly Topology Preserving Map , 1995, Neural Computation.

[151]  Shigeo Abe,et al.  A method for fuzzy rules extraction directly from numerical data and its application to pattern classification , 1995, IEEE Trans. Fuzzy Syst..

[152]  James C. Bezdek,et al.  On cluster validity for the fuzzy c-means model , 1995, IEEE Trans. Fuzzy Syst..

[153]  R. Wong,et al.  Use, disuse, and growth of the brain. , 1995, Proceedings of the National Academy of Sciences of the United States of America.

[154]  Joachim Diederich,et al.  Survey and critique of techniques for extracting rules from trained artificial neural networks , 1995, Knowl. Based Syst..

[155]  S. Pinker The language instinct : how the mind creates language , 1995 .

[156]  Robert F. Port,et al.  Mind as motion: The dynamics of cognition. , 1995 .

[157]  Kishan G. Mehrotra,et al.  Efficient classification for multiclass problems using modular neural networks , 1995, IEEE Trans. Neural Networks.

[158]  Sandiway Fong,et al.  Natural language grammatical inference: a comparison of recurrent neural networks and machine learning methods , 1995, Learning for Natural Language Processing.

[159]  W. Hauptmann,et al.  A neural net topology for bidirectional fuzzy-neuro transformation , 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

[160]  Nicholas R. Jennings,et al.  Intelligent agents: theory and practice , 1995, The Knowledge Engineering Review.

[161]  M.H. Hassoun,et al.  Fundamentals of Artificial Neural Networks , 1996, Proceedings of the IEEE.

[162]  A. Konnerth,et al.  Long-term potentiation and functional synapse induction in developing hippocampus , 1996, Nature.

[163]  Enrico Blanzieri,et al.  Learning Radial Basis Function Networks On-line , 1996, International Conference on Machine Learning.

[164]  Friedrich Ungerer,et al.  An introduction to cognitive linguistics , 1999 .

[165]  Masumi Ishikawa,et al.  Structural learning with forgetting , 1996, Neural Networks.

[166]  J. Collado-Vides Integrative Approaches to Molecular Biology , 1996 .

[167]  S. Grossberg,et al.  The Hippocampus and Cerebellum in Adaptively Timed Learning, Recognition, and Movement , 1996, Journal of Cognitive Neuroscience.

[168]  Vassilios Digalakis,et al.  Adaptive speech recognition to a speaker. , 1996 .

[169]  Terrence J. Sejnowski,et al.  The Computational Brain , 1996, Artif. Intell..

[170]  Joseph Montanarella,et al.  Artificial Intelligence : A Knowledge-Based Approach , 1996 .

[171]  Andreas Ziehe,et al.  Adaptive On-line Learning in Changing Environments , 1996, NIPS.

[172]  David G. Stork,et al.  Speechreading by Humans and Machines , 1996 .

[173]  Javier R. Movellan,et al.  Dynamic Features for Visual Speechreading: A Systematic Comparison , 1996, NIPS.

[174]  Juergen Luettin,et al.  Active Shape Models for Visual Speech Feature Extraction , 1996 .

[175]  James R. Koehler,et al.  Statistics in Engineering: A Practical Approach , 1996 .

[176]  Jacek M. Zurada,et al.  Pruning via Dynamic Adaptation of the Forgetting Rate in Structural Learning , 1996, Proceedings of International Conference on Neural Networks (ICNN'96).

[177]  Stephen T. Neely,et al.  Signals, Sound, and Sensation , 1997 .

[178]  Michael J. Watts,et al.  FuNN/2 - A Fuzzy Neural Network Architecture for Adaptive Learning and Knowledge Acquisition , 1997, Inf. Sci..

[179]  Nicolaos B. Karayiannis,et al.  Growing radial basis neural networks: merging supervised and unsupervised learning with network growth techniques , 1997, IEEE Trans. Neural Networks.

[180]  Teuvo Kohonen,et al.  Self-Organizing Maps, Second Edition , 1997, Springer Series in Information Sciences.

[181]  Michael J. Watts,et al.  Genetic algorithms for structural optimisation, dynamic adaptation and automated design of fuzzy neural networks , 1997, Proceedings of International Conference on Neural Networks (ICNN'97).

[182]  Dorothea Heiss-Czedik,et al.  An Introduction to Genetic Algorithms. , 1997, Artificial Life.

[183]  John G. Taylor,et al.  Neural networks for consciousness , 1997, Neural Networks.

[184]  Nikola Kasabov,et al.  Chapter 5 A Framework for Intelligent " Conscious " Machines Utilising Fuzzy Neural Networks and Spatial-Temporal Maps and a Case Study of Multilingual Speech Recognition , 1997 .

[185]  László T. Kóczy,et al.  Fuzzy systems and approximation , 1997, Fuzzy Sets Syst..

[186]  Joy Hirsch,et al.  Distinct cortical areas associated with native and second languages , 1997, Nature.

[187]  CHEE PENG LIM,et al.  An Incremental Adaptive Network for On-line Supervised Learning and Probability Estimation , 1997, Neural Networks.

[188]  D. Parisi An Artificial Life Approach to Language , 1997, Brain and Language.

[189]  Kumar S. Ray,et al.  Neuro Fuzzy Approach to Pattern Recognition , 1997, Neural Networks.

[190]  Gerald Sommer,et al.  An integrated architecture for learning of reactive behaviors based on dynamic cell structures , 1997, Robotics Auton. Syst..

[191]  Nikola Kasabov,et al.  Neuro-fuzzy methods for environmental modelling , 1997 .

[192]  Toshio Fukuda,et al.  Stabilization control of biped locomotion robot based learning with GAs having self-adaptive mutation and recurrent neural networks , 1997, Proceedings of International Conference on Robotics and Automation.

[193]  Christopher M. Bishop,et al.  GTM: The Generative Topographic Mapping , 1998, Neural Computation.

[194]  Nikola Kasabov,et al.  Evolving Fuzzy Neural Networks : Theory and Applications for On-line Adaptive Prediction , Decision Making and Control , 1998 .

[195]  Michael J. Watts,et al.  Genetic Algorithms for the Design of Fuzzy Neural Networks , 1998, ICONIP.

[196]  D. Botstein,et al.  The transcriptional program of sporulation in budding yeast. , 1998, Science.

[197]  Ronald W. Davis,et al.  A genome-wide transcriptional analysis of the mitotic cell cycle. , 1998, Molecular cell.

[198]  Christopher R. Stephens,et al.  Self-Adaptation in Evolving Systems , 1997, Artificial Life.

[199]  P G Baker,et al.  Recent developments in biological sequence databases. , 1998, Current opinion in biotechnology.

[200]  Michael Ruogu Zhang,et al.  Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. , 1998, Molecular biology of the cell.

[201]  Nikola K. Kasabov,et al.  The ECOS Framework and the ECO Learning Method for Evolving Connectionist Systems , 1998, Journal of Advanced Computational Intelligence and Intelligent Informatics.

[202]  Frithjof Kruggel,et al.  Neuronal and Hemodynamic Events from fMRI Time-Series , 1998, J. Adv. Comput. Intell. Intell. Informatics.

[203]  Irena Koprinska,et al.  Video segmentation of MPEG compressed data , 1998, 1998 IEEE International Conference on Electronics, Circuits and Systems. Surfing the Waves of Science and Technology (Cat. No.98EX196).

[204]  Samuel Russell Hampden Joseph,et al.  Theories of adaptive neural growth , 1998 .

[205]  Michael A. Gibson,et al.  Modeling the Activity of Single Genes , 1999 .

[206]  Hiroshi Okamoto,et al.  Temporal Event Association and Output-Dependent Learning: A Proposed Scheme of Neural Molecular Connections , 1999, J. Adv. Comput. Intell. Intell. Informatics.

[207]  LiMin Fu,et al.  An expert network for DNA sequence analysis , 1999, IEEE Intell. Syst..

[208]  N. Kasabov,et al.  Rule insertion and rule extraction from evolving fuzzy neural networks: algorithms and applications for building adaptive, intelligent expert systems , 1999, FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315).

[209]  J. Mesirov,et al.  Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. , 1999, Science.

[210]  G. Church,et al.  Systematic determination of genetic network architecture , 1999, Nature Genetics.

[211]  Nikola K. Kasabov,et al.  From hybrid adjustable neuro-fuzzy systems to adaptive connectionist-based systems for phoneme and word recognition , 1999, Fuzzy Sets Syst..

[212]  Nikola K. Kasabov,et al.  HyFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems , 1999, Neural Networks.

[213]  R. Miesfeld,et al.  Applied Molecular Genetics , 1999 .

[214]  U. Alon,et al.  Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[215]  John G. Taylor The race for consciousness , 1999 .

[216]  Nikola Kasabov,et al.  Neuro-Fuzzy Techniques for Intelligent Information Systems , 1999 .

[217]  H. M. Wain Introduction to Bioinformatics. Cell and Molecular Biology in Action Series. By T. K. Attwood and D. J. Parry‐Smith (Series Editor: E. Wood). Harlow, Essex: Addison Wesley Longman. 1999. Pp. 218. £17.99 (paperback). , 1999 .

[218]  Gwi-Tae Park,et al.  An adaptive fuzzy controller for power converters , 1999, FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315).

[219]  John J. Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities , 1999 .

[220]  Peter W. Culicover,et al.  Syntactic Nuts: Hard Cases, Syntactic Theory, and Language Acquisition , 1999 .

[221]  Eric O. Postma,et al.  AVIS: a connectionist-based framework for integrated auditory and visual information processing , 2000, Inf. Sci..

[222]  Sushmita Mitra,et al.  Neuro-fuzzy rule generation: survey in soft computing framework , 2000, IEEE Trans. Neural Networks Learn. Syst..

[223]  Patrik D'haeseleer,et al.  Genetic network inference: from co-expression clustering to reverse engineering , 2000, Bioinform..

[224]  Eric O. Postma,et al.  Discovering the Visual Signature of Painters , 2000 .

[225]  Roland Somogyi,et al.  Genetic network inference , 2000 .

[226]  C. Macilwain World leaders heap praise on human genome landmark , 2000, Nature.

[227]  Andreas D. Baxevanis,et al.  The Molecular Biology Database Collection: an online compilation of relevant database resources , 2000, Nucleic Acids Res..

[228]  Christian A. Rees,et al.  Molecular portraits of human breast tumours , 2000, Nature.

[229]  Cathy H. Wu,et al.  Neural networks and genome informatics , 2000 .

[230]  Irena Koprinska,et al.  Evolving fuzzy neural network for camera operations recognition , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[231]  Nikola Kasabov,et al.  Modelling the Emergence of Speech and Language Through Evolving Connectionist Systems , 2000 .

[232]  Nikola Kasabov,et al.  A Methodology and a System for Adaptive Speech Recognition in a Noisy Environment Based on Adaptive Noise Cancellation and Evolv- ing Fuzzy Neural Networks , 2000 .

[233]  Jacek M. Zurada,et al.  Knowledge-based neurocomputing , 2000 .

[234]  Abraham Kandel,et al.  Neuro-Fuzzy Pattern Recognition , 2000 .

[235]  D. Floreano,et al.  Evolutionary Robotics: The Biology,Intelligence,and Technology , 2000 .

[236]  Andrew D. Back,et al.  A spiking neural network architecture for nonlinear function approximation , 2001, Neural Networks.

[237]  Tadashi Kitamura,et al.  What should be computed to understand and model brain function?: from robotics, soft computing, biology and neuroscience to cognitive philosophy , 2001 .

[238]  Nikola Kasabov,et al.  Brain-like functions in evolving connectionist systems for on-line, knowledge-based learning , 2001 .

[239]  Fred Henrik Hamker,et al.  Life-long learning Cell Structures--continuously learning without catastrophic interference , 2001, Neural Networks.

[240]  M. Tomita Whole-cell simulation: a grand challenge of the 21st century. , 2001, Trends in biotechnology.

[241]  Vojislav Kecman Support Vector Machines , 2001 .

[242]  Pierre Baldi,et al.  Bioinformatics - the machine learning approach (2. ed.) , 2001 .

[243]  R. Spang,et al.  Predicting the clinical status of human breast cancer by using gene expression profiles , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[244]  J. Mendel Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions , 2001 .

[245]  Erkki Oja,et al.  Independent Component Analysis , 2001 .

[246]  Nikola Kasabov,et al.  Evolving connectionist systems , 2002 .

[247]  Nikola K. Kasabov,et al.  DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction , 2002, IEEE Trans. Fuzzy Syst..

[248]  Petra Perner,et al.  Data Mining - Concepts and Techniques , 2002, Künstliche Intell..

[249]  James C. Schaff,et al.  The Virtual Cell , 2002, Annals of the New York Academy of Sciences.

[250]  Nikola Kasabov,et al.  Fuzzy clustering of gene expression data , 2002, 2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291).

[251]  Nikola K. Kasabov,et al.  Evolving connectionist systems for knowledge discovery from gene expression data of cancer tissue , 2003, Artif. Intell. Medicine.

[252]  Nikola K. Kasabov,et al.  On-line pattern analysis by evolving self-organizing maps , 2003, Neurocomputing.

[253]  Karin Ackermann,et al.  Categories and Concepts , 2003, Job 28. Cognition in Context.

[254]  Waleed H. Abdulla,et al.  Reduced feature-set based parallel CHMM speech recognition systems , 2003, Inf. Sci..

[255]  G. Lewicki,et al.  Approximation by Superpositions of a Sigmoidal Function , 2003 .

[256]  Richard Kilgour,et al.  Evolving systems for connectionist-based speech recognition , 2003 .

[257]  Gerald Sommer,et al.  On-line Learning with Dynamic Cell Structures , 2004 .

[258]  S.-I. Amari,et al.  Neural theory of association and concept-formation , 1977, Biological Cybernetics.

[259]  W. Freeman Simulation of chaotic EEG patterns with a dynamic model of the olfactory system , 1987, Biological Cybernetics.

[260]  Teuvo Kohonen,et al.  Self-organized formation of topologically correct feature maps , 2004, Biological Cybernetics.

[261]  T. Houtgast,et al.  Integration of visual and auditory information in speech perception , 2004 .

[262]  Roman Borisyuk,et al.  Bifurcation analysis of a neural network model , 1992, Biological Cybernetics.

[263]  Jude W. Shavlik,et al.  Extracting Refined Rules from Knowledge-Based Neural Networks , 1993, Machine Learning.

[264]  J. Ross Quinlan,et al.  Induction of Decision Trees , 1986, Machine Learning.

[265]  G. Schneider,et al.  Development of artificial neural filters for pattern recognition in protein sequences , 1993, Journal of Molecular Evolution.

[266]  Kunihiko Fukushima,et al.  A neural network model for selective attention in visual pattern recognition , 1986, Biological Cybernetics.

[267]  Roman Rosipal,et al.  Prediction of Chaotic Time-Series with a Resource-Allocating RBF Network , 1998, Neural Processing Letters.